The right to feel safe and secure is one of the most important basic principles in society, and this is where surveillance systems have an important function, as long as they are used in accordance with prevailing legislation. There is an ongoing debate about the implications of surveillance on privacy. Recent developments in network camera technology have led to several different applications that can be implemented to limit surveillance and thus protect privacy. One such development is privacy masking, which enables selected areas of a scene to be blocked or masked from viewing and recording. It allows masking to be maintained even as a field of view of the image capturing device (e.g. a video camera) changes through panning, tilting and zooming as the masking moves with the coordinate system of the device. Privacy masking may be achieved by blurring pixels within a privacy area of the captured images, so specific details (such as a face of a person) in this area cannot be deciphered or interpreted by a user looking at the video stream.
When applying privacy masking, care should be taken to not to blur image data in the privacy area more than necessary, to still be able use the captured video for surveillance purposes in the best possible way. This may be achieved by limiting the degree of blurring applied to the privacy area of the image based on blur in the image already being present due to the current settings and hardware of the image capturing device (e.g. parts of the image being unfocused or having low spatial resolution).
US2015085163 (Canon) discloses one solution to how to limit the degree of blurring. This document discloses a method where imaging data is analysed to determine if there is a privacy protection target present, i.e. a detected face. A focus range corresponding to the currently used F-number is determined. If the protection target is located within the focus range, a relatively large blur amount is added. If the protection target is located outside the focus range, a lower (or no) blur amount is added since the target will be blurred to some degree already. US2015085163 teaches that a predetermined look-up-table is used to determine the amount of added blur needed for different F-number settings and distances from the best focus position. The method in US2015085163 is complex, since a protection target needs to be determined, and the distance to this target needs to be calculated, before the blurring of the area of the image where the protection target is present can be determined. Moreover, the predetermined look-up-table reduces the flexibility of the method and requires specific look-up table for every camera system. Furthermore, different use cases require different amount of blurring being present in a privacy area. For example, a use case involving blurring of number plates of a car may require a different amount of blurring to be impossible to decipher compared to a use case involving blurring of a face of a person.
There is thus a need for improvements within this context.